Search Results for author:
Found 5 papers, 2 papers with code
Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning
We introduce Deep Reasoning Networks (DRNets), an end-to-end framework that combines deep learning with constraint reasoning for solving pattern de-mixing problems, typically in an unsupervised or very-weakly-supervised setting.
Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction
Modern machine learning techniques have been extensively applied to materials science, especially for property prediction tasks.
Exponentially-Modified Gaussian Mixture Model: Applications in Spectroscopy
In particular, we demonstrate the effectiveness of PMF in conjunction with the EMG mixture model on synthetic data and two real-world applications: X-ray diffraction and Raman spectroscopy.
End-to-End Refinement Guided by Pre-trained Prototypical Classifier
We propose imitation refinement, a novel approach to refine imperfect input patterns, guided by a pre-trained classifier incorporating prior knowledge from simulated theoretical data, such that the refined patterns imitate the ideal data.
Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery
A key problem in materials discovery, the phase map identification problem, involves the determination of the crystal phase diagram from the materials' composition and structural characterization data.
